发表机构
Utsunomiya University; Aichi Institute of Technology（宇都宫大学; 爱知工业大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对多关节仿生水下机器人运动控制依赖预设规则的问题，提出基于传感器模态和势函数的多模态控制器，实现游泳与步态行为转换，并经物理与仿真验证。
AI 中文摘要
多模态仿生水下机器人（BURs）能够执行适应环境的水下任务。结合水生生物的特征，可实现水下探索所需的游泳和腿部运动。其运动控制机制依赖于基于规则的行为选择和设计者的判断，这限制了机器人获取新行为能力的范围，使其局限于预定的行为集合。为解决这些挑战，我们提出了一种机构与控制系统，能够从相同的多关节结构中表达多模态运动能力。该机构配备四条腿鳍，每条腿鳍具有四个轴。该控制器基于传感器模态实现非线性行为，而非依赖于基于运动功能的预定义条件规则。该系统通过基于多种传感器数据和行为模式的物理测试与仿真测试进行了验证。利用势函数进行多模态运动控制，已验证能够实现两种或三种行为之间的转换。将该控制方法实现为多模态控制器，有望增强其在水下探索中的应用。我们的项目页面位于此 https URL。
英文摘要
Multimodal biomimetic underwater robots (BURs) can conduct underwater tasks suitable for the environment. Combining the characteristics of aquatic organisms enables the swimming and leggedlocomotion required for underwater exploration. Locomotion control mechanism relies on rule-based behavior selection and the designer's discretion. This limits the robot's ability to acquire new behavioral capabilities to the predetermined range of behaviors. To address these challenges, we propose a mechanism and control system that enables the expression of multimodal locomotion capabilities from the same multi-jointed structure. A mechanism equipped with four leg-fins each having four axes is used. This controller achieves nonlinear behavior based on sensor modalities, rather than relying on predefined conditional rule-based on locomotion functions. This system was validated through both physical and simulation testing based on multiple sensor data and behavioral patterns. Utilizing a potential function in multimodal locomotion control was verified to enable transitions between two or three behaviors. Implementing the control method as a multimodal controller is expected to enhance its application in underwater exploration. Our project page is at https://tasada038.github.io/multi-jointed-bur/.
CommentsPreprint version of an article published in Advanced Robotics (2026)
Journal refAdvanced Robotics (2026)
DOI：10.1080/01691864.2026.2728312
